Autonomous driving system

ABSTRACT

An autonomous driving system includes a normal driving situation determination unit configured to determine whether or not autonomous driving is in a normal driving situation, a driver situation recognition unit configured to recognize a driver situation, a distrust determination unit configured to determine whether or not the driver is in a system distrust state, based on a recognition result obtained by the driver situation recognition unit, and a warning control unit configured to output an alert in accordance with the external environment of the vehicle when the normal driving situation determination unit determines that autonomous driving is in the normal driving situation and the distrust determination unit determines that the driver is in the system distrust state.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of priority from Japanese PatentApplication No. 2019-005232, filed Jan. 16, 2019, the entire contents ofwhich are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to an autonomous driving system.

BACKGROUND

In the related art, Japanese Unexamined Patent Publication No.2015-032054 is known as technical literature relating to an autonomousdriving system. The publication discloses an over-dependence deterrencedevice which determines the driver's overconfidence in a driving supportsystem that supports driving of a vehicle, and when it is determinedthat the driver is in an overconfidence state, performs at least one ofa warning to the driver that the driver is in the overconfidence stateand suppression of driving support control.

SUMMARY

Incidentally, in recent years, a development of an autonomous drivingsystem capable of performing autonomous driving under certainconditions, has been promoted. In such an autonomous driving, if thesystem makes false attention awakening, the driver may not trust theautonomous driving system. When the driver has a distrust of theautonomous driving system, a problem occurs that the driver does nottrust the warning of the system, thus it is desired to handle the aboveissue.

Therefore, in the technical field, it is desired to provide anautonomous driving system that can eliminate a system distrust state ofthe driver during autonomous driving.

An aspect of the present disclosure is an autonomous driving system thatperforms autonomous driving of a vehicle and performs various warningsto a driver of the vehicle during autonomous driving, the systemincluding a vehicle position recognition unit configured to recognize aposition of the vehicle on a map, an external environment recognitionunit configured to recognize an external environment of the vehicle, atravel state recognition unit configured to recognize a travel state ofthe vehicle, a trajectory generation unit configured to generate atrajectory of the vehicle used for the autonomous driving, based on mapinformation, the position of the vehicle on the map, the externalenvironment of the vehicle, and the travel state of the vehicle, anormal driving situation determination unit configured to determinewhether or not autonomous driving is in a normal driving situation,based on at least one of the position of the vehicle on the map, theexternal environment of the vehicle, the travel state of the vehicle,and the trajectory of the vehicle, a driver situation recognition unitconfigured to recognize a driver situation including at least one of adriving action time of the driver, a non-driving action time of thedriver, and a reaction delay time of the driver with respect to a changein the external environment of the vehicle, a distrust determinationunit configured to determine whether or not the driver is in a systemdistrust state, based on a recognition result obtained by the driversituation recognition unit, and a warning control unit configured tooutput an alert in accordance with the external environment of thevehicle, when the normal driving situation determination unit determinesthat autonomous driving is in the normal driving situation and thedistrust determination unit determines that the driver is in the systemdistrust state.

According to the autonomous driving system according to the aspect ofthe present disclosure, an alert is output in accordance with theexternal environment of the vehicle, when the normal driving situationdetermination unit determines that autonomous driving is in the normaldriving situation and the distrust determination unit determines thatthe driver is in the system distrust state. In this way, in theautonomous driving system, it is possible to appropriately eliminate thesystem distrust state of the driver during autonomous driving byencouraging the driver who is in the system distrust state by outputtingthe alert in accordance with the external environment while ensuringthat autonomous driving is in the normal driving situation.

In the autonomous driving system according to the aspect of the presentdisclosure, a system confidence degree calculation unit is furtherincluded to be configured to calculate a system confidence degreeregarding the autonomous driving based on at least one of the positionof the vehicle on the map, the external environment of the vehicle, thetravel state of the vehicle, and the trajectory of the vehicle, and thenormal driving situation determination unit may determine thatautonomous driving is not in the normal driving situation, when thesystem confidence degree is lower than a normal driving threshold value.

In the autonomous driving system according to the aspect of the presentdisclosure, an anxiety elicitation situation determination unit isfurther included to be configured to determine whether or not thevehicle during autonomous driving is in an anxiety elicitation situationbased on the external environment of the vehicle, and the warningcontrol unit outputs the alert when the anxiety elicitation situationdetermination unit determines that the vehicle is in the anxietyelicitation situation in case where the normal driving situationdetermination unit determines that autonomous driving is in the normaldriving situation and the distrust determination unit determines thatthe driver is in the system distrust state, and may not output the alertwhen the anxiety elicitation situation determination unit determinesthat the vehicle is not in the anxiety elicitation situation, in casewhere the normal driving situation determination unit determines thatautonomous driving is in the normal driving situation and the distrustdetermination unit determines that the driver is in the system distruststate

In the autonomous driving system according to the aspect of the presentdisclosure, the anxiety elicitation situation determination unitdetermines that the vehicle during autonomous driving is in the anxietyelicitation situation, if an area of a moving object in a captured imageby a camera that images the front of the vehicle as the externalenvironment of the vehicle is equal to or greater than an anxietyelicitation threshold value.

According to the aspect of the present disclosure, it is possible toeliminate the system distrust state of the driver during autonomousdriving.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an autonomous driving systemaccording to a first embodiment.

FIG. 2 is a diagram for explaining a driving action time and anon-driving action time.

FIG. 3 is a diagram for explaining an example of an anxiety elicitationsituation.

FIG. 4 is a flowchart illustrating an example of autonomous drivingprocessing.

FIG. 5 is a flowchart illustrating an example of alert outputprocessing.

FIG. 6 is a flowchart illustrating an example of system distrust statedetermination processing.

FIG. 7A is a flowchart illustrating an example of reference reactiondelay time storage processing.

FIG. 7B is a flowchart illustrating another example of system distruststate determination processing.

FIG. 8 is a flowchart illustrating an example of anxiety elicitationsituation determination processing.

DETAILED DESCRIPTION

Hereinafter, embodiments of the present disclosure will be describedwith reference to the drawings.

FIG. 1 is a block diagram illustrating an autonomous driving systemaccording to a first embodiment. An autonomous driving system 100illustrated in FIG. 1 is mounted on a vehicle such as a passenger car,and performs autonomous driving of the vehicle. Autonomous driving is avehicle control that causes the vehicle to autonomously travel toward adestination set in advance. During autonomous driving, the driver doesnot need to perform a driving operation of steering, and the vehicletravels autonomously. In addition, the autonomous driving system 100performs various warnings to the driver of the vehicle during autonomousdriving. Details of the warning will be described below.

Configuration of Autonomous Driving System

As illustrated in FIG. 1, the autonomous driving system 100 includes anelectronic control unit (ECU) 20 that performs overall management of thesystem. The ECU 20 is an electronic control unit including a centralprocessing unit (CPU), a read only memory (ROM), a random access memory(RAM), and the like. In the ECU 20, for example, various functions arerealized by loading a program stored in the ROM into the RAM and causingthe CPU to execute the program loaded in the RAM. The ECU 20 may beconfigured with a plurality of electronic units.

The ECU 20 is connected to a GPS receiver 1, an external sensor 2, aninternal sensor 3, a map database 4, a driving operation detection unit5, a driver monitor camera 6, a voice recognition unit 7, an in-vehiclecommunication unit 8, an actuator 9, and a human machine interface (HMI)10.

The GPS receiver 1 measures a position of the vehicle (for example, thelatitude and longitude of the vehicle) by receiving signals from threeor more GPS satellites. The GPS receiver 1 transmits the measuredposition information of the vehicle to the ECU 20. Instead of the GPSreceiver 1, a global navigation satellite system (GNSS) receiver may beused.

The external sensor 2 is a detection device that detects a surroundingsituation of the vehicle. The external sensor 2 includes at least one ofa camera and a radar sensor.

The camera is an imaging device that images an external situation of thevehicle. The camera is provided on the inside of a windshield of thevehicle. The camera transmits imaging information on the externalsituation of the vehicle to the ECU 20. The camera may be a monocularcamera or a stereo camera.

The radar sensor is a detection device that detects objects around thevehicle using at least one of radio waves (for example, millimeterwaves) and light. The radar sensor includes, for example, at least oneof the millimeter wave radar and a light detection and ranging (LIDAR).The radar sensor transmits at least one of the radio wave and the lightto the surroundings of the vehicle, and detects the objects by receivingradio waves or light reflected from the objects. The radar sensortransmits the detected object information to the ECU 20. The objectsinclude fixed objects such as guard rails and buildings, as well asmoving objects such as pedestrians, bicycles, and other vehicles. Theexternal sensor 2 does not necessarily need to include the radar sensor.

The internal sensor 3 is a detection device that detects a travel stateof the vehicle. The internal sensor 3 includes a vehicle speed sensor,an acceleration sensor, and a yaw rate sensor. The vehicle speed sensoris a measuring device that measures a speed of the vehicle. As thevehicle speed sensor, for example, a vehicle wheel speed sensor is used,which is provided in at least one of the vehicle wheels of the vehicleand a drive shaft rotating integrally with vehicle wheels, and measuresa rotational speed of the vehicle wheels. The vehicle speed sensortransmits the measured vehicle speed information to the ECU 20.

The acceleration sensor is a measuring device that measures anacceleration of the vehicle. The acceleration sensor includes, forexample, a longitudinal acceleration sensor that measures accelerationin a longitudinal direction of the vehicle and a lateral accelerationsensor that measures a lateral acceleration of the vehicle. Theacceleration sensor transmits, for example, the acceleration informationof the vehicle to the ECU 20. The yaw rate sensor is a measuring devicethat measures a yaw rate (rotation angular velocity) around the verticalaxis at the center of gravity of the vehicle. As the yaw rate sensor,for example, a gyro sensor can be used. The yaw rate sensor transmitsthe measured yaw rate information of the vehicle to the ECU 20.

The map database 4 is a database that stores map information. The mapdatabase 4 is formed, for example, in a hard disk drive (HDD) mounted onthe vehicle. The map information includes position information on alane, information on a shape of the lane (for example, a curve, a lanewidth, or the like), position information on a stop line, information onpositions of an intersection and a branch, and position information onstructures. The map information may also include speed relatedinformation such as a legal speed associated with at least one of theposition and a section on the map. The map information may also includeposition information on marking objects such as utility poles, used forvehicle position recognition. The map database 4 may be stored in aserver that can communicate with the vehicle.

The driving operation detection unit 5 detects the operation of theoperation unit of the vehicle by the driver. The driving operationdetection unit 5 includes, for example, a steering sensor, anaccelerator sensor, and a brake sensor. The operation unit of thevehicle is a device to which the driver inputs the operation for drivingthe vehicle. The operation unit of the vehicle includes at least one ofa steering unit of the vehicle, an accelerator operation unit of thevehicle, and a brake operation unit of the vehicle. The steering unitis, for example, a steering wheel. The steering unit is not limited tohave a wheel shape, but need only have a configuration that functions asa steering wheel. The accelerator operation unit is, for example, anaccelerator pedal. The brake operation unit is, for example, a brakepedal. The accelerator operation unit and the brake operation unit donot necessarily need to be pedals, and need only have a configuration inwhich the driver can input acceleration or deceleration.

The steering sensor includes a steering touch sensor that detectsgripping of the steering unit of the driver. For example, a capacitancetype touch sensor can be used as the steering touch sensor. The steeringtouch sensor is provided on the left and right sides of the steeringunit to detect the gripping of the driver's hands. The steering sensormay measure an operation amount of the steering unit by the driver. Theoperation amount of the steering unit includes at least one of asteering angle and a steering torque.

The accelerator sensor measures an operation amount of the acceleratoroperation unit by the driver. The operation amount of the acceleratoroperation unit includes, for example, a depression amount of theaccelerator pedal. The brake sensor measures an operation amount of thebrake operation unit by the driver. The operation amount of the brakeoperation unit includes, for example, a depression amount of the brakepedal. The operation amounts of the accelerator operation unit and thebrake operation unit may include the depression speed. The drivingoperation detection unit 5 transmits operation amount information on themeasured operation amount by the driver to the ECU 20.

The driver monitor camera 6 is an imaging device that images the driverof the vehicle. The driver monitor camera 6 is provided, for example, atthe position of the front of the driver on the cover of a steeringcolumn of the vehicle, and images the driver. A plurality of drivermonitor cameras 6 may be provided to image the driver from a pluralityof directions. The driver monitor camera 6 transmits imaging informationon the driver to the ECU 20. The autonomous driving system 100 does notnecessarily need to use the driver monitor camera 6.

The voice recognition unit 7 is a device that recognizes the voice of anoccupant in the vehicle compartment. The voice recognition unit 7includes, for example, a microphone for collecting the voice in thevehicle compartment. A plurality of microphones may be provided in thevehicle compartment. The voice recognition unit 7 transmits the resultof the recognition of the voice of the occupant in the vehiclecompartment to the ECU 20. The voice recognition unit 7 does notnecessarily need to recognize the voice of the occupant as a language,and may only determine whether or not the occupants are in conversation.The voice recognition unit 7 may have a personal authentication functionusing a voice, and may determine whether or not the driver is inconversation based on the voice.

The voice recognition unit 7 may be, for example, always in a voicerecognition state, and may function as a so-called smart speaker. Inaddition, the voice recognition unit 7 may configure a part of the HMI10 described below. The voice recognition unit 7 may recognize a sound(such as a traveling sound of another vehicle, an engine sound ofanother vehicle, or the like) reaching the vehicle compartment from theoutside of the vehicle. The autonomous driving system 100 does notnecessarily need to use the voice recognition unit 7.

The in-vehicle communication unit 8 is a device for the ECU 20 tocommunicate with various information terminals in the vehicle. Thevarious information terminals include, for example, at least one ofsmartphones, tablet personal computers, and wearable devices owned bythe occupant. The wearable devices include watch-type wearable devices,glasses-type wearable devices, and the like. The in-vehiclecommunication unit 8 communicates with the information terminals toacquire information such as whether or not the smartphones are inoperation. The in-vehicle communication unit 8 may acquire driver'sbiometric information by communicating with the wearable devices. Thebiometric information includes at least one of heartbeat, brain waves,blood pressure, body temperature, and the like. The in-vehiclecommunication unit 8 transmits the various information acquired by thecommunication to the ECU 20. The autonomous driving system 100 does notnecessarily need to use the in-vehicle communication unit 8.

The actuator 9 is a device used to control the vehicle. The actuator 9includes at least a throttle actuator, a brake actuator, and a steeringactuator. The throttle actuator controls a driving force of the vehicleby controlling an amount of air (throttle opening degree) supplied tothe engine according to the control signal from the ECU 20. If thevehicle is a hybrid vehicle, in addition to the amount of air suppliedto the engine, the control signal from the ECU 20 is input to a motor asa power source, and the driving force of the vehicle is controlled. Ifthe vehicle is an electric vehicle, the control signal from the ECU 20is input to a motor as a power source instead of the throttle actuator,and the driving force of the vehicle is controlled. The motor as thepower source in these cases configures the actuator 9.

The brake actuator controls the brake system according to the controlsignal from the ECU 20 and controls a braking force applied to thewheels of the vehicle. For example, a hydraulic brake system can be usedas the brake system. The steering actuator controls the driving of anassist motor that controls the steering torque of an electric powersteering system, according to the control signal from the ECU 20.

The HMI 10 is a device to perform input and output of the informationbetween the autonomous driving system 100 and the occupant. The HMI 10includes a display 10 a, a speaker 10 b, and a vibrator 10 c.

The display 10 a is a display provided in the vehicle. The display 10 ais provided, for example, on a dashboard of the vehicle. The display 10a performs various image displays according to the control signal fromthe ECU 20. The display 10 a may be a head-up display that projects anddisplays an image on the windshield of the vehicle. The display 10 a mayinclude a multi-information display provided on an instrument panel ofthe vehicle. The display 10 a may include a blind spot monitor providedon side view mirrors of the vehicle.

The speaker 10 b is a voice output device provided in the vehicle. Thespeaker 10 b is provided, for example, on the inside of the door of thevehicle and on the back of the instrument panel. The speaker 10 bperforms various voice outputs according to the control signal from theECU 20.

The vibrator 10 c is a vibration actuator for performing a warning tothe driver by outputting the vibration. The vibration actuator isprovided, for example, on at least one of the steering unit of thevehicle, a seat of the driver's seat, a headrest of the driver's seat,an armrest of the driver's seat, the accelerator pedal, and the brakepedal. The vibrator 10 c outputs the vibration according to the controlsignal from the ECU 20. The HMI 10 does not necessarily need to includethe vibrator 10 c.

Next, a functional configuration of the ECU 20 will be described. TheECU 20 includes a vehicle position recognition unit 21, an externalenvironment recognition unit 22, a travel state recognition unit 23, atrajectory generation unit 24, a vehicle control unit 25, a systemconfidence degree calculation unit 26, a normal driving situationdetermination unit 27, and a driver situation recognition unit 28, adistrust determination unit 29, an anxiety elicitation situationdetermination unit 30, and a warning control unit 31. A part of thefunctions of the ECU 20 described below may be performed on the servercapable of communicating with the vehicle.

The vehicle position recognition unit 21 recognizes the position of thevehicle on the map based on the position information in the GPS receiver1 and the map information in the map database 4. In addition, thevehicle position recognition unit 21 may estimate the position of thevehicle on the map by the simultaneous localization and mapping (SLAM)technology using the position information of the marking object includedin the map information in the map database 4 and the result of thedetection performed by the external sensor 2. The vehicle positionrecognition unit 21 may recognize the position of the vehicle on the mapby a well-known method.

The external environment recognition unit 22 recognizes the externalenvironment around the vehicle based on the result of the detection (theobject information by the radar sensor and/or the imaging information bythe camera) performed by the external sensor 2. The external environmentincludes a situation of objects around the vehicle. The situation of theobject refers to, for example, a relative position and a relative speedof the object to the vehicle.

The external environment may include recognition results of lane lines(a lane boundary line, a center line, and the like) around the vehicle.The external environment recognition unit 22 recognizes the relativeposition of the lane line to the vehicle by well-known white linerecognition based on the result of the detection performed by theexternal sensor 2. The external environment recognition unit 22 mayrecognize a sound reaching the vehicle compartment from the outside ofthe vehicle, which is recognized by the voice recognition unit 7, as apart of the external environment. If an external sound detector (such asa microphone) that detects the sounds outside the vehicle is provided inthe vehicle, the external environment recognition unit 22 may recognizethe sounds detected by the external sound detector as a part of theexternal environment.

The travel state recognition unit 23 recognizes the state of thetraveling vehicle based on the result of the detection performed by theinternal sensor 3. The travel state includes the speed of the vehicle,the acceleration of the vehicle, and the yaw rate of the vehicle.Specifically, the travel state recognition unit 23 recognizes the speedof the vehicle based on the vehicle speed information from the vehiclespeed sensor. The travel state recognition unit 23 recognizes theacceleration (a longitudinal acceleration and a lateral acceleration) ofthe vehicle based on the acceleration information from the accelerationsensor. The travel state recognition unit 23 recognizes the yaw rate ofthe vehicle based on the yaw rate information from the yaw rate sensor.

The trajectory generation unit 24 generates a trajectory to be used forthe autonomous driving of the vehicle. The trajectory generation unit 24generates the trajectory for the autonomous driving based on adestination set in advance, the map information in the map database 4,the position of the vehicle on the map recognized by vehicle positionrecognition unit 21, the external environment of vehicle recognized byexternal environment recognition unit 22, and the travel state (thevehicle speed, the yaw rate, and the like) recognized by the travelstate recognition unit 23. The destination may be set by the occupant ofthe vehicle, or may be proposed by at least one of the autonomousdriving system 100 and a well-known navigation system.

The trajectory generation unit 24 obtains a traveling route for theautonomous driving based on the destination, the map information, andthe position of the vehicle on the map. The traveling route is a routeon which the vehicle travels by autonomous driving, and is a route fromthe position of the vehicle on the map (the current position) to thedestination. The traveling route may be set by a well-known navigationsystem. The traveling route can be represented as a route on alane-by-lane basis, for example. The trajectory generation unit 24generates a trajectory for autonomous driving of the vehicle along thetraveling route based on the map information.

The trajectory includes a path on which the vehicle travels byautonomous driving, and the vehicle speed profile during autonomousdriving. The path is a trajectory on which the vehicle during autonomousdriving is planned to travel on the traveling route. The path can bedata of the steering angle change (a steering angle profile) of thevehicle corresponding to the position on the traveling route, forexample. The position on the traveling route is, for example, a setlongitudinal position which is set at predetermined intervals (forexample, 1 m) in the traveling direction of the traveling route. Thesteering angle profile is data in which the target steering angle isassociated with each set longitudinal position.

The trajectory generation unit 24 generates the path on which thevehicle travels, based on the traveling route, the map information, theexternal environment of the vehicle, and the travel state of thevehicle, for example. The trajectory generation unit 24 generates thepath such that the vehicle passes through the center of the laneincluded in the traveling route.

The vehicle speed profile is data in which a target vehicle speed isassociated with each set longitudinal position, for example. The setlongitudinal position may be set based on the traveling time of thevehicle instead of the distance. The set longitudinal position may beset as an arrival position of the vehicle after 1 seconds and thearrival position of the vehicle after 2 seconds.

The trajectory generation unit 24 generates the vehicle speed profilebased on, for example, speed related information such as a legal speedincluded in the path and the map information. Instead of the legalspeed, a set speed may be used, which is set in advance for at least oneof the position and the section on the map. The trajectory generationunit 24 generates the trajectory for the autonomous driving based on thepath and the vehicle speed profile. The trajectory is not limited to thedescription above. The trajectory need only include informationnecessary to realize the autonomous driving of the vehicle.

The vehicle control unit 25 performs the autonomous driving of thevehicle. The vehicle control unit 25 performs the autonomous driving ofthe vehicle based on the map information, the position of the vehicle onthe map, the external environment of the vehicle, the travel state ofthe vehicle, and the trajectory. The vehicle control unit 25 performsthe autonomous driving along the trajectory generated by the trajectorygeneration unit 24 and autonomously performs emergency avoidance and thelike in an emergency. The vehicle control unit 25 performs theautonomous driving of the vehicle by transmitting the control signals tothe actuator 9.

The system confidence degree calculation unit 26 calculates a systemconfidence degree regarding the autonomous driving by the autonomousdriving system 100 based on at least one of the position of the vehicleon the map, the external environment of the vehicle, the travel state ofthe vehicle, and the trajectory of the vehicle. The system confidencedegree is an index indicating the reliability (certainty) of theautonomous driving in the autonomous driving system 100. The systemconfidence degree corresponds to the possibility of continuity ofautonomous driving.

If the system confidence degree falls below a termination thresholdvalue, the autonomous driving system 100 may end the autonomous drivingcontrol and switch the driving mode to a driver-based driving. Thedriver-based driving includes manual driving by a driver (full manualdriving) and driving by a driver supported by a driving support controlsuch as adaptive cruise control (ACC) and lane keeping assist (LKA). Thetermination threshold value is a threshold value of a value set inadvance. Hereinafter, various “threshold values” used in the descriptionof the present specification mean threshold values set in advance.

The system confidence degree calculation unit 26 calculates the systemconfidence degree based on, for example, the external environment of thevehicle recognized by the external environment recognition unit 22.Specifically, when the number of moving objects such as other vehiclesaround the vehicle is equal to or greater than a certain number, thesystem confidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when the number of movingobjects around the vehicle is less than the certain number. If there isa preceding vehicle within a certain distance in front of the vehicle,the system confidence degree calculation unit 26 may calculate thesystem confidence degree as a lower value compared to when there is nopreceding vehicle.

If there is a preceding vehicle within a certain distance in front ofthe vehicle, the system confidence degree calculation unit 26 maycalculate the system confidence degree as a lower value, as thevehicle-to-vehicle distance between the vehicle and the precedingvehicle becomes shorter. If there is a following vehicle within acertain distance behind the vehicle, the system confidence degreecalculation unit 26 may calculate the system confidence degree as alower value compared to when there is no following vehicle. If there isa parallel traveling vehicle that travels side by side with the vehicle,the system confidence degree calculation unit 26 may calculate thesystem confidence degree as a lower value compared to when there is noparallel traveling vehicle.

If there is an object in front of the vehicle with a time to collision(TTC) shorter than a TTC threshold value, the system confidence degreecalculation unit 26 may calculate the system confidence degree as alower value compared to when there is no object in front of the vehiclewith a time to collision shorter than the TTC threshold value. Thevehicle-to-vehicle time may be used instead of the time to collision.

If there is a pedestrian within a certain distance from the vehicle inthe traveling direction of the vehicle, the system confidence degreecalculation unit 26 may calculate the system confidence degree as alower value compared to a case where there is no pedestrian. If there isa pedestrian moving in the direction crossing the trajectory of thevehicle, the system confidence degree calculation unit 26 may calculatethe system confidence degree as a lower value compared to when there isno pedestrian. The same can be applied to bicycles and a personalmobility instead of the pedestrians.

If another vehicle around the vehicle performs abnormal behavior, thesystem confidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when the other vehicledoes not perform the abnormal behavior. The abnormal behavior is anunusual behavior that another vehicle is not supposed to do in astandard traveling situation. The abnormal behavior can include rapiddeceleration, rapid acceleration, rapid steering, lighting of a hazardlamp, and the like. If another vehicle around the vehicle deviates fromthe normal behavior set in advance, the system confidence degreecalculation unit 26 may recognize that the abnormal behavior is beingperformed. The normal behavior can refer to that, for example, theacceleration and deceleration is equal to or lower than the thresholdvalue, and refer to traveling along the lane at a speed equal to orlower than the legal maximum speed of the lane.

If the shielding ratio of the detection range of the external sensor 2due to the buildings, other vehicles, or the like is equal to or higherthan a shielding threshold value, the system confidence degreecalculation unit 26 may calculate the system confidence degree as alower value compared to when the shielding ratio of the detection rangeof the external sensor 2 is lower than the shielding threshold value.The system confidence degree calculation unit 26 may recognize a markingobject included in the detection range of the external sensor 2 on themap, based on the position of the vehicle on the map and the positioninformation of the marking object included in the map information, andmay compare the result of the recognition with the marking object (astationary object) recognized by the external environment recognitionunit 22. If a difference number obtained by subtracting the number ofmarking objects recognized by the external environment recognition unit22 from the number of marking objects included in the detection range ofexternal sensor 2 on the map is equal to or greater than a differencethreshold value, the system confidence degree calculation unit 26 maycalculate the system confidence degree as a lower value compared to whenthe difference number is less than the difference threshold value. Thesystem confidence degree calculation unit 26 may recognize the number ofmarking objects included in the detection range of the external sensor 2on the map in consideration of the shielding of the detection range ofthe external sensor 2 due to the buildings or the like.

The system confidence degree calculation unit 26 may calculate thesystem confidence degree based on a tracking situation of the movingobjects such as other vehicles as the external environment of thevehicle. If the moving object being tracked within the detection rangeof external sensor 2 is lost, the system confidence degree calculationunit 26 may calculate the system confidence degree as a lower valuecompared to when the moving object is not lost. If at least one of theshape or the volume of the moving object being tracked is changed toequal to or higher than a certain percentage, since it is likely toerroneously recognize a plurality of objects as one moving object, thesystem confidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when at least one of theshape and the volume of the moving object is not changed. If a relativespeed of the moving object being tracked is changed suddenly, since itis likely to erroneously recognize the plurality of objects havingdifferent speed as one object, the system confidence degree calculationunit 26 may calculate the system confidence degree as a lower valuecompared to when the relative speed of the moving object is not changedsuddenly. For example, when the speed change within a certain period oftime is equal to or greater than a sudden change threshold value, thesystem confidence degree calculation unit 26 can recognize that therelative speed has suddenly changed.

If the external environment of the vehicle includes the result of therecognition of a traffic signal in front of the vehicle, and if theshape of the recognized traffic signal does not match the shape of thetraffic signal stored in the map information (for example, when therecognized traffic signal is a three-light type with an arrow light, andthe traffic signal stored in the map information is a three-light typewithout an arrow light), the system confidence degree calculation unit26 may calculate the system confidence degree as a lower value comparedto when the shape of the recognized traffic signal matches the shape ofthe traffic signal stored in the map information. The dimension of thetraffic signal may be considered as well as the shape of the trafficsignal. In addition, instead of the traffic signal, at least one of theshape and the dimension of the marking object may be used.

If the external environment of the vehicle includes the weather aroundthe vehicle, the system confidence degree calculation unit 26 maycalculate the system confidence degree as a lower value when the weatheraround the vehicle is rainy compared to when the weather around thevehicle is clear. The weather around the vehicle can be determined basedon at least one of the imaging information by the camera and the resultof the detection performed by the radar sensor. The weather around thevehicle may be determined based on an operation situation of thewindshield wiper of the vehicle.

The system confidence degree calculation unit 26 may calculate thesystem confidence degree based on a degree of interference of the movingobject with respect to the trajectory of the vehicle. The degree ofinterference of the moving object with respect to the trajectory of thevehicle can be calculated, for example, by using the method disclosed inJapanese Patent Publication No. 2007-230454. The system confidencedegree calculation unit 26 calculates the system confidence degree as alower value, for example, as the degree of interference of the movingobject with respect to the trajectory of the vehicle becomes higher.

The system confidence degree calculation unit 26 may calculate thesystem confidence degree based on a degree of danger of the movingobject around the vehicle. The degree of danger of the moving objectaround the vehicle can be calculated, for example, by using the methoddisclosed in Japanese Patent No. 2008-158969. The system confidencedegree calculation unit 26 calculates the system confidence degree as alower value, for example, as the degree of danger of the moving objectwith respect to the trajectory of the vehicle becomes higher.

The system confidence degree calculation unit 26 may calculate thesystem confidence degree based on the position of the vehicle on the maprecognized by the vehicle position recognition unit 21. For example, ifthe position recognition of the vehicle is performed using a markingobject in addition to the position information in the GPS receiver 1,the system confidence degree calculation unit 26 calculates the systemconfidence degree as a lower value compared to when the position of thevehicle is recognized using only the position information in the GPSreceiver 1.

If the vehicle is positioned in the area where the accuracy of the mapinformation is low, the system confidence degree calculation unit 26 maycalculate the system confidence degree as a lower value compared to whenthe vehicle is positioned in other areas. The information regardingwhether or not the accuracy of map information is low is associated withthe map information in advance, for example. If the number of GPSsatellites from which the GPS receiver 1 receives the signals is equalto or greater than a GPS threshold value, the system confidence degreecalculation unit 26 may calculate the system confidence degree as alower value compared to when the number of GPS satellites is less thanthe GPS threshold value. If the arrangement of the GPS satellites fromwhich GPS receiver 1 receives the signals is dispersed, the systemconfidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when the arrangement ofthe GPS satellites is concentrated.

If the number of the recognized marking objects positioned around thevehicle is less than a marking object threshold value, the systemconfidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when the number of therecognized marking objects is equal to or greater than the markingobject threshold value. If a positional relationship between a pluralityof the recognized marking objects around the vehicle does not match apositional relationship between each of the marking objects in mapinformation, the system confidence degree calculation unit 26 maycalculate the system confidence degree as a lower value compared to whenthe positional relationship between the plurality of the recognizedmarking objects matches the positional relationship between each of themarking objects in the map information. When the positional relationshipbetween the plurality of the recognized marking objects around thevehicle does not match the positional relationship between each of themarking objects in map information, and if an average of position errorsof each marking object is shorter than a certain distance, the systemconfidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when the average of theposition errors of each marking object is equal to or longer than acertain distance. A median value or a total value may be used instead ofthe average.

When the vehicle is positioned in a complicated road environment such asintersections, crossings, merging points, and branches, the systemconfidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when the vehicle is notpositioned in the complicated road environment. If the vehicle ispositioned in the poor visibility area set in the map information inadvance, the system confidence degree calculation unit 26 calculates thesystem confidence degree as a lower value compared to when the vehicleis not positioned in the poor visibility area.

The system confidence degree calculation unit 26 may calculate thesystem confidence degree based on the travel state of the vehiclerecognized by the travel state recognition unit 23. If the measurementresult of the speed of the vehicle is an abnormal value, the systemconfidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when the measurementresult of the vehicle speed is not the abnormal value. For example, whena difference between the vehicle speed measured before one frame and thecurrently measured vehicle speed is equal to or higher than anabnormality detection threshold value (for example, 20 km/h or higher),the system confidence degree calculation unit 26 recognizes that themeasured vehicle speed is the abnormal value. The same is applied to theacceleration and the yaw rate.

The system confidence degree calculation unit 26 may calculate thesystem confidence degree from the result of comparison between thetravel state of the vehicle which is planned in the travel plan and thetravel state of the vehicle which is recognized as a result ofperforming the autonomous driving control, based on the travel state ofthe vehicle recognized by the travel state recognition unit 23 and thetravel plan generated by the travel plan generation unit 34. Forexample, if a deviation between the vehicle speed planned in the travelplan and the history of the vehicle speed as a result of autonomousdriving control is equal to or greater than a deviation threshold value,the system confidence degree calculation unit 26 may calculate thesystem confidence degree as a lower value compared to when the deviationis less than the deviation threshold value. The same is applied to theacceleration and the yaw rate.

In addition, when abnormalities are detected in various sensors (theexternal sensor, the internal sensor, and the like) of the vehicle, thesystem confidence degree calculation unit 26 may calculate the systemconfidence degree as a lower value compared to when various sensors arenormal. Well-known abnormality detection technology can be used fordetecting the abnormalities of the sensors.

The system confidence degree calculation unit 26 calculates (predicts)the system confidence degree corresponding to the position (a futureposition) on the trajectory of the vehicle. The position on thetrajectory of the vehicle is, for example, the position of the vehiclein the travel plan at a plurality of future times set in advance andseparated by a predetermined time. The predetermined time may be, forexample, 1 seconds, or may be 0.5 seconds. The predetermined time may beshorter as the speed of the vehicle increases. The number of futuretimes need only be equal to or greater than two.

Alternatively, the position on the trajectory of the vehicle may be aplurality of positions separated by a predetermined interval startingfrom the vehicle on the trajectory of the vehicle. The predeterminedinterval may be, for example, 10 m, or may be 15 m. The number ofpositions for which the system confidence degree is calculated may befixed or may be changed according to the speed of the vehicle. Thenumber of positions for which the system confidence degree is calculatedmay increase as the speed of the vehicle increases.

The system confidence degree calculation unit 26 can calculate a futuresystem confidence degree in the position on the trajectory of thevehicle by predicting the behavior of the moving objects around thevehicle based on the external environment of the vehicle. The systemconfidence degree calculation unit 26 estimates the number of movingobjects around the vehicle for each position of the vehicle on thetrajectory by, for example, predicting the behavior of the movingobjects around the vehicle. If the estimated number of moving objects isequal to or greater than a certain number, the system confidence degreecalculation unit 26 calculates the system confidence degree at thatposition as a lower value compared to when the estimated number ofmoving objects around the vehicle is less than the certain number.

The system confidence degree calculation unit 26 may determine whetheror not there is a preceding vehicle within a certain distance from thevehicle for each position of the vehicle on the trajectory based on theprediction of the behavior of another vehicle around the vehicle, andthen, may calculate the system confidence degree for each position ofthe vehicle on the trajectory based on the determination result of thepresence or absence of the preceding vehicle. In addition, the systemconfidence degree calculation unit 26 may estimate thevehicle-to-vehicle distance between the vehicle and the precedingvehicle based on the prediction of the behavior of the preceding vehiclefor each position of the vehicle on the trajectory, and may calculatethe system confidence degree for each position of the vehicle on thetrajectory based on the estimation result of the vehicle-to-vehicledistance between the vehicle and the preceding vehicle. The same can beapplied to the calculation of the following vehicle and the paralleltraveling vehicle.

The system confidence degree calculation unit 26 may estimate the timeto collision between the vehicle and the moving object for each positionof the vehicle on the trajectory to use the time to collision forcalculating the system confidence degree. By considering the mapinformation including the position information of the stationary objectin addition to the prediction of the behavior of the moving objects, thesystem confidence degree calculation unit 26 may predict the shieldingratio of the detection range of external sensor 2 for each position ofthe vehicle of the trajectory to use the result of prediction forcalculating the system confidence degree. The system confidence degreecalculation unit 26 may calculate the system confidence degree for eachposition of the vehicle on the trajectory using at least one of thedegree of interference of the moving object with respect to thetrajectory of the vehicle described above and the degree of danger ofthe moving object around the vehicle.

The system confidence degree calculation unit 26 may calculate thesystem confidence degree for each position of the vehicle on thetrajectory based on the map information. The system confidence degreecalculation unit 26 predicts the number of marking objects that can berecognized for each position of the vehicle on the trajectory based onthe map information, for example. If the number of marking objects thatcan be recognized at a certain position on the trajectory is less than amarking object threshold value, the system confidence degree calculationunit 26 may calculate the system confidence degree at that position as alower value compared to when the number of marking objects is equal toor greater than the marking object threshold value. If the position ofthe vehicle on the trajectory is included in an area where the accuracyof the map information is low, the system confidence degree calculationunit 26 may calculate the system confidence degree at that position as alower value compared to when the position is not included in the areawhere the accuracy of the map information is low. If the position of thevehicle on the trajectory is positioned in a complicated roadenvironment, the same can be applied to the case where the position ofthe vehicle on the trajectory is positioned in an area having poorvisibility.

The normal driving situation determination unit 27 determines whether ornot autonomous driving is in the normal driving situation, based on atleast one of the position of the vehicle on the map, the externalenvironment of the vehicle, the travel state of the vehicle, and thetrajectory of the vehicle. The normal driving situation is a situationin which autonomous driving is normally operated in the autonomousdriving system 100. The fact that autonomous driving is in the normaldriving situation means that the autonomous driving of the vehicle isnormally operated, and means that it is not a situation in which thedriving mode is switched to the driver-based driving due to the suddentermination of autonomous driving.

Specifically, the normal driving situation determination unit 27determines whether or not autonomous driving is in the normal drivingsituation, based on the system confidence degree calculated from atleast one of the position of the vehicle on the map, the externalenvironment of the vehicle, the travel state of the vehicle, and thetrajectory of the vehicle. For example, if the system confidence degreeis equal to or higher than a normal driving threshold value, the normaldriving situation determination unit 27 determines that autonomousdriving is in the normal driving situation. If the system confidencedegree is lower than the normal driving threshold value, the normaldriving situation determination unit 27 determines that autonomousdriving is not in the normal driving situation.

The normal driving situation determination unit 27 may determine whetheror not autonomous driving is in the normal driving situation withoutusing the system confidence degree. For example, if the shielding ratioof the detection range of the external sensor 2 due to the buildings,other vehicles, or the like is equal to or greater than the shieldingthreshold value, the normal driving situation determination unit 27 maydetermine that autonomous driving is not in the normal drivingsituation. In a sensor abnormality is detected in at least one of theexternal sensor 2 and the internal sensor 3, the normal drivingsituation determination unit 27 may determine that autonomous driving isnot in the normal driving situation.

The normal driving situation determination unit 27 may determine whetheror not autonomous driving is in the normal driving situation based on anaccuracy of the recognition of the position of the vehicle on the map bythe vehicle position recognition unit 21. The normal driving situationdetermination unit 27 obtains the accuracy of the recognition of theposition of the vehicle on the map based on the number of the recognizedmarking objects positioned around the vehicle and/or the arrangement ofthe marking objects around the vehicle. If the accuracy of therecognition is lower than a recognition accuracy threshold value, thenormal driving situation determination unit 27 determines thatautonomous driving is not in the normal driving situation.

The normal driving situation determination unit 27 may determine whetheror not autonomous driving is in the normal driving situation based onthe trajectory generated by the trajectory generation unit 24. Forexample, if a deviation width (a distortion width) in the right and leftdirection of the trajectory within a certain distance is equal to orgreater than a deviation width threshold value, the normal drivingsituation determination unit 27 determines that autonomous driving isnot in the normal driving situation. If a difference between the speedupper limit and the speed lower limit in the trajectory within a certaindistance is equal to or higher than a speed difference threshold value,the normal driving situation determination unit 27 may determine thatautonomous driving is not in the normal driving situation.

In addition, the normal driving situation determination unit 27 maycalculate a traveling safety degree of the trajectory generated by thetrajectory generation unit 24 by using trajectory evaluation methoddisclosed in Japanese Unexamined Patent Publication No. 2009-157502. Inthis case, for example, if the traveling safety degree of the trajectoryadopted for autonomous driving is lower than a traveling safety degreethreshold value, the normal driving situation determination unit 27 candetermine that autonomous driving is not in the normal drivingsituation.

The normal driving situation determination unit 27 may determine whetheror not autonomous driving is in the normal driving situation bycombining a plurality of criteria such as the shielding ratio of thedetection range of external sensor 2, the accuracy of the recognition ofthe position of the vehicle on the map, the trajectory, and likedescribed above, in addition to the system confidence degree. If it isdetermined that autonomous driving is not in the normal drivingsituation based on any one of the criteria, the normal driving situationdetermination unit 27 may determine that autonomous driving is not inthe normal driving situation regardless of the result of thedetermination based on other criteria.

The driver situation recognition unit 28 recognizes a driver situationduring autonomous driving. The result of the recognition of the driversituation is used in the distrust determination by the distrustdetermination unit 29 described below. The driver situation includes atleast one of a driving action time of the driver, a non-driving actiontime of the driver, and a reaction delay time of the driver with respectto changes in the external environment of the vehicle. The driversituation recognition unit 28 recognizes the driver situation based onat least one of the driver's operation detected by the driving operationdetection unit 5 and the driver image captured by the driver monitorcamera 6. The driver situation may include a warning reaction delay timeof the driver to the warning.

First, the driving action of the driver will be described. The drivingaction of the driver is an action for which the driver drives thevehicle. The driving action includes an action in which the driver gripsthe steering unit of the vehicle and an action in which the drivermonitors the front of the vehicle and the like. The driver situationrecognition unit 28 detects the driving action of the driver based on,for example, at least one of the driver's operation detected by thedriving operation detection unit 5 and the driver image captured by thedriver monitor camera 6. For example, if the driver is in a drivingposture in which the driver grips the steering unit of the vehicle withboth hands while the driver faces the front of the vehicle, the driversituation recognition unit 28 detects that the driver is performing adriving action. The driver situation recognition unit 28 recognizes thetime when the driving action of the driver is detected, as the drivingaction time.

Next, the non-driving action time of the driver will be described. Thenon-driving action time of the driver is a time during which the driveris performing non-driving action. The non-driving action is an actionthat is not related to a driving action. The non-driving action includeslooking aside, an operation of a smartphone, an operation of a vehiclefacility (for example, an audio facility or a navigation system) and thelike.

The driver situation recognition unit 28 recognizes the non-drivingaction time by detecting the non-driving action of the driver based on,for example, the driver image captured by the driver monitor camera 6.If the in-vehicle communication unit 8 is communicating with thedriver's smartphone, the driver situation recognition unit 28 may detectthe non-driving action of the driver from the operation information ofthe smartphone of the driver. The driver situation recognition unit 28may detect the non-driving action of the driver using both the operationinformation of the smartphone of the driver and the driver imagecaptured by the driver monitor camera 6.

The driver situation recognition unit 28 may detect the non-drivingaction of the driver from the operation information of the vehiclefacility. If it is determined that the driver is concentrating on theconversation based on the result of the recognition performed by thevoice recognition unit 7, the driver situation recognition unit 28 maydetect such a situation as the non-driving action of the driver. Thefact that the driver is concentrating on the conversation is a state inwhich, for example, the driver is speaking continuously with a voice ofa certain volume or higher. The voice of the driver may be registered inthe voice recognition unit 7 in advance. The driver situationrecognition unit 28 may determine whether or not the driver isconcentrating on the conversation by combining the driver image capturedby the driver monitor camera 6 and the result of the recognitionperformed by the voice recognition unit 7.

Next, the reaction delay time of the driver to the changes in theexternal environment of the vehicle will be described. The changes inthe external environment of the vehicle mean the changes in the externalenvironment to which the driver takes reaction. The changes in theexternal environment of the vehicle include at least one of aninterruption of another vehicle in front of the vehicle, running out ofthe pedestrian in front of the vehicle, an overtaking of another vehiclebeside the vehicle, a rapid deceleration of the preceding vehicle, andthe like. The driver situation recognition unit 28 recognizes that thechanges in the external environment of the vehicle have occurred basedon the external environment of the vehicle recognized by the externalenvironment recognition unit 22.

The driver situation recognition unit 28 may distinguish and recognizethe types of changes in the external environment of the vehicle. In thiscase, the interruption of another vehicle in front of the vehicle, therunning out of the pedestrian in front of the vehicle, the overtaking ofanother vehicle beside the vehicle, and the rapid deceleration of thepreceding vehicle can be recognized as a different type of changes ofthe external environment with each other. The running out of thepedestrian may be the same type as the running out of the moving objectssuch as a bicycle, a personal mobility, or another vehicle.

The reaction delay time of the driver is a delay time from theoccurrence of the changes in the external environment of the vehicle tothe reaction of the driver. For example, if the driver is in a drivingposture in which the driver grips the steering unit of the vehicle withboth hands while the driver faces the front of the vehicle, the driversituation recognition unit 28 detects that the driver takes the reactionto the changes in the external environment of the vehicle. The driversituation recognition unit 28 may detect that the driver takes thereaction when the driver faces the front of the vehicle, regardless ofthe situation of the driver's hand. Alternatively, the driver situationrecognition unit 28 may detect that the driver takes the reaction whenthe driver grips the steering unit with both hands without recognizingthe orientation of the driver's face.

In addition, the driver situation recognition unit 28 may detect thatthe driver takes the reaction when the driver moves the face so as tocheck the surroundings of the vehicle. When the brake sensor detectsthat the driver puts his/her foot on the brake pedal or when theaccelerator sensor detects that the driver puts his/her foot on theaccelerator pedal, the driver situation recognition unit 28 may detectthat the driver takes the reaction.

If it is determined that the driver visually recognizes the changes inthe external environment of the vehicle, the driver situationrecognition unit 28 may detect that the driver takes the reaction. Forexample, if the changes in the external environment of the vehicle isanother vehicle's overtaking, the driver situation recognition unit 28detects that the driver takes the reaction to the overtaking of theother vehicle when the driver turns the face toward the other vehicle.If the reaction delay time of the driver to the changes in the externalenvironment of the vehicle is recognized, the warning to the driver thatwill be described below is not performed. In addition, the driversituation recognition unit 28 may recognize driver's biometricinformation through the communication with the wearable device attachedto the driver through the in-vehicle communication unit 8.

Next, the warning reaction delay time of the driver to the warning willbe described. The warning is, for example, a notification for performingattention awakening to the driver of the changes in the externalenvironment of the vehicle. The changes in the external environment ofthe vehicle in this case can also include at least one of theinterruption of another vehicle in front of the vehicle, the running outof the pedestrian in front of the vehicle, the overtaking of anothervehicle beside the vehicle, and the rapid deceleration of the precedingvehicle. The changes in the external environment of the vehicle meansthe changes in the external environment to which the driver takesreaction and the changes in the external environment of the vehiclewhich is a warning target do not necessarily need to match each other.For example, if the interruption of another vehicle in front of thevehicle is recognized, the autonomous driving system 100 performs thewarning to the driver for attention awakening. The content of thewarning will be described below.

The warning reaction delay time of the driver is a delay time from theoutput of the warning to the time of driver's reaction. The driver'sreaction can be recognized in the same manner as the reaction delay timeof the driver described above. If the warning is an image display, thedriver situation recognition unit 28 may detect that the driver takesthe reaction when the driver turns the face in the direction where theimage is displayed. If the warning is a voice output, the driversituation recognition unit 28 may detect that the driver takes thereaction when the driver turns the face in the direction where the voiceis output. The driver situation recognition unit 28 recognizes the timefrom the warning output to the time of the recognition of the driver'sreaction as the warning reaction delay time of the driver to thewarning. The driver situation recognition unit 28 does not necessarilyneed to recognize the reaction delay time and the warning reaction delaytime.

The distrust determination unit 29 determines whether or not the driveris in the system distrust state based on the result of the recognitionperformed by the driver situation recognition unit 28. The systemdistrust state is a state in which the driver has a distrust withrespect to autonomous driving by the autonomous driving system 100.

Specifically, the distrust determination unit 29 determines whether ornot the driver is in the system distrust state based on the drivingaction time of the driver. The distrust determination unit 29 calculatesa length of the driving action time of the driver in a certain periodduring autonomous driving. The distrust determination unit 29 determinesthat the driver is in the system distrust state when the length of thedriving action time of the driver in a certain period is equal to orlonger than the driving action threshold value. The driving actionthreshold value is a threshold value of a value set in advance.

Here, FIG. 2 is a diagram for explaining a driving action time and anon-driving action time. A driving action time Td and a non-drivingaction time Ts are illustrated in FIG. 2. In FIG. 2, when a driver'sdriving action is detected, the driver situation recognition unit 28recognizes the time of driver's driving action as the driving actiontime Td. A surroundings monitoring action is a part of the drivingaction. If the driver's non-driving action is detected, the driversituation recognition unit 28 recognizes the time of driver'snon-driving action as the non-driving action time Ts. As illustrated inFIG. 2, the driver's action during autonomous driving can be dividedinto the driving action and the non-driving action, for example. In thedriver in the system distrust state, since it is considered that thedriving action time Td in a certain period during autonomous drivingincreases, it is possible to determine whether or not the driver is inthe system distrust state based on the driving action time Td.

In a situation illustrated in FIG. 2, the distrust determination unit 29determines that the driver is in the system distrust state when, forexample, the length of the driving action time Td of the driver in acertain period is equal to or longer than the driving action thresholdvalue.

The distrust determination unit 29 may determine whether or not thedriver is in the system distrust state based on the driver's non-drivingaction time Ts. The distrust determination unit 29 determines that thedriver is in the system distrust state when the length of thenon-driving action time Ts of the driver in a certain period is shorterthan the non-driving action threshold value. The non-driving actionthreshold value is a threshold value of a value set in advance.

The distrust determination unit 29 may determine whether or not thedriver is in the system distrust state based on the driving action timeTd of the driver and the non-driving action time Ts of the driver. Thedistrust determination unit 29 calculates a ratio of the driving actiontime Td and the non-driving action time Ts in a certain period duringautonomous driving. For example, if a ratio of non-driving action timeTs to the driving action time Td is less than a ratio threshold value,the distrust determination unit 29 determines that the driver is in thesystem distrust state. The ratio threshold value is a threshold value ofa value set in advance. The ratio threshold value may be 0.2 or 0.3. Acertain period may be several tens of minutes, one hour, or the entireperiod after autonomous driving starts.

The distrust determination unit 29 may determine whether or not thedriver is in the system distrust state based on a result of comparisonbetween the reaction delay time of the driver to the changes in theexternal environment of the vehicle and the warning reaction delay timeof the driver. It is considered that the driver in the system distruststate is not just dependent on the warning from the autonomous drivingsystem 100, but reacts quickly to changes in the external environment ofthe vehicle. Therefore, by comparing the reaction delay time of thedriver to the changes in the external environment of the vehicle and thewarning reaction delay time of the driver, it is possible to determinewhether or not the driver is in the system distrust state.

In this case, first, if the driver situation recognition unit 28recognizes the warning reaction delay time of the driver to the warningin accordance with the changes in the external environment of thevehicle, the distrust determination unit 29 stores the warning reactiondelay time of the driver as a reference reaction delay time. Thedistrust determination unit 29 may store the reference reaction delaytime in a storage device connected to the ECU 20.

Thereafter, if the driver situation recognition unit 28 recognizes thereaction delay time of the driver to the changes in the externalenvironment of the vehicle, the distrust determination unit 29calculates a difference obtained by subtracting the reaction delay timefrom the reference reaction delay time (stored warning reaction delaytime). If the driver quickly responds to changes in the externalenvironment, the difference obtained by subtracting the reaction delaytime of the driver from the reference reaction delay time is a positivevalue, and it is considered that the difference increases as the driverreacts more quickly. If the difference obtained by subtracting thereaction delay time from the reference reaction delay time is equal toor greater than the distrust threshold value, the distrust determinationunit 29 determines that the driver is in the system distrust state. Thedistrust threshold value is a threshold value having a positive value.The distrust threshold value may be changed in accordance with variousparameters such as the speed of the vehicle or the brightness of theoutside of the vehicle.

The distrust determination unit 29 may distinguish the types of changesin the external environment of the vehicle. The distrust determinationunit 29 stores the warning reaction delay time of the driver for eachtype of the interruption of another vehicle in front of the vehicle, therunning out of the pedestrian in front of the vehicle, the overtaking ofanother vehicle beside the vehicle, the rapid deceleration of thepreceding vehicle, and the like. If the driver situation recognitionunit 28 recognizes the reaction delay time of the driver to the changesin the external environment of the vehicle, the distrust determinationunit 29 determines whether or not the driver is in the system distruststate by comparing the recognized reaction delay time of the driver withthe warning reaction delay time corresponding to the type of change ofthe external environment.

The distrust determination unit 29 does not necessarily need to performthe comparison between the reaction delay time of the driver and thewarning reaction delay time of the driver. The distrust determinationunit 29 may determine whether or not the driver is in the systemdistrust state based on the reaction delay time of the driver to thechanges in the external environment of the vehicle.

Specifically, the distrust determination unit 29 stores the reactiondelay time for the comparison for each type of the changes in theexternal environment of the vehicle. If the reaction delay time of thedriver to the changes in the external environment of the vehicle isrecognized, the distrust determination unit 29 calculates a differenceobtained by subtracting the reaction delay time of the driver from thereaction delay time for comparison corresponding to the type of changeof the external environment. If the difference obtained by subtractingthe reaction delay time of the driver from the reaction delay time forcomparison is equal to or greater than the distrust threshold value, thedistrust determination unit 29 may determine that the driver is in thesystem distrust state. The distrust determination unit 29 may use thereaction delay time for comparison having different values depending onthe type of changes in the external environment of the vehicle.

Similarly, the distrust determination unit 29 may determine whether ornot the driver is in the system distrust state based on the warningreaction delay time of the driver to the warning corresponding to thechanges in the external environment of the vehicle. The distrustdetermination unit 29 stores the warning reaction delay time forcomparison, in advance. If the warning reaction delay time of the driveris recognized, the distrust determination unit 29 calculates adifference obtained by subtracting the warning reaction delay time ofthe driver from the warning reaction delay time for comparison. If thedifference obtained by subtracting the warning reaction delay time ofthe driver from the warning reaction delay time for comparison is equalto or greater than the distrust threshold value, the distrustdetermination unit 29 may determine that the driver is in the systemdistrust state. The distrust determination unit 29 may use the warningreaction delay time for comparison having different values depending onthe type of changes in the external environment of the vehicle.

In addition, the distrust determination unit 29 may determine the systemdistrust state based on the biometric information of the driverrecognized by the driver situation recognition unit 28, in addition tothe driving action time. The distrust determination unit 29 maydetermine the system distrust state by using the biometric informationof the driver in combination with the driving action time, or the like.If an armrest sensor that measures the weight of the driver's arm isprovided on the armrest of the driver's seat, the distrust determinationunit 29 may determine the system distrust state using the result ofmeasurement performed by the armrest sensor in combination with thedriving action time, or the like. When the driver does not lean on thearmrest, it can be considered that the driver is more likely to be inthe system distrust state than when the driver leans on the armrest.

The anxiety elicitation situation determination unit 30 determineswhether or not the vehicle during autonomous driving is in an anxietyelicitation situation, based on the external environment of the vehicle.The anxiety elicitation situation is a situation of the vehicle thatcauses an anxiety to the driver of the vehicle. The anxiety elicitationsituation is determined from the viewpoint of the driver. Examples ofthe anxiety elicitation situation include a situation in which anothervehicle is trying to interrupt in front of the vehicle within thedriver's field of view and the vehicle and the other vehicle are closeto each other.

For example, based on the image captured by the camera that captures thefront of the vehicle, if the area of the moving object in the capturedimage is equal to or greater than the anxiety elicitation thresholdvalue, the anxiety elicitation situation determination unit 30determines that the vehicle during autonomous driving is in the anxietyelicitation situation. The area of the moving object is an area occupiedby the moving objects such as other vehicles, pedestrians, bicycles(movable obstacles), and the like in the captured image. The anxietyelicitation situation determination unit 30 can determine the anxietyelicitation situation based on the area of the moving object, from afact that the driver is likely to be more anxious about the situation ofthe vehicle as the area of the moving object that occupies the field ofview of the driver increases.

Here, FIG. 3 is a diagram for explaining an example of the anxietyelicitation situation. FIG. 3 illustrates an image G captured by acamera, a preceding vehicle N1, a right side other vehicle N2, and aleft side other vehicle N3. Furthermore, FIG. 3 illustrates an imagearea A1 of the preceding vehicle N1, an image area A2 of the right sideother vehicle N2, and an image area A3 of the left side other vehicleN3. The area of the moving object is the total area of the image areasA1 to A3.

In the situation in FIG. 3, the anxiety elicitation situationdetermination unit 30 recognizes an area of the moving object (the totalarea of the image areas A1 to A3) in the image G captured by the camera,based on the external environment of the vehicle recognized by theexternal environment recognition unit 22. If the area of the movingobject is equal to or greater than the anxiety elicitation thresholdvalue, the anxiety elicitation situation determination unit 30determines that the vehicle is in the anxiety elicitation situation. Theanxiety elicitation threshold value may be changed in accordance withvarious parameters such as at least one of the speed of the vehicle andthe brightness of the outside of the vehicle. Well-known imagerecognition technology may be used to recognize the area of the movingobject in the captured image.

The anxiety elicitation situation determination unit 30 may determinethat the vehicle is in the anxiety elicitation situation when the areaof the moving object suddenly increases. For example, if the increase inthe area of the moving object within a certain period of time is equalto or greater than an area increase threshold value, the anxietyelicitation situation determination unit 30 determines that the vehicleis in the anxiety elicitation situation.

In addition, the anxiety elicitation situation determination unit 30 mayconsider the area of not only the image captured by the camera thatimages the front of the vehicle but also the area of the moving objectin the image captured by a camera that images at least one of the sideor rear of the vehicle. For example, if the area of the moving object,which is the sum of the image areas of the moving objects captured byall the cameras that images the outside of the vehicle, is equal to orgreater than the anxiety elicitation threshold value, the anxietyelicitation situation determination unit 30 may determine that thevehicle during autonomous driving is in the anxiety elicitationsituation.

The anxiety elicitation situation determination unit 30 does notnecessarily need to determine the anxiety elicitation situation based onthe area of the moving object. The anxiety elicitation situationdetermination unit 30 may determine the anxiety elicitation situationwhile considering the density of other vehicles around the vehicle,types of other vehicles around the vehicle, and a sound around thevehicle. As an example, an anxiety elicitation degree can be used. Ifthe anxiety elicitation degree is equal to or higher than an anxietyelicitation degree threshold value, the anxiety elicitation situationdetermination unit 30 determines that the vehicle is in the anxietyelicitation situation.

The anxiety elicitation situation determination unit 30 calculates theanxiety elicitation degree as a large value when the type of the othervehicle positioned within a certain distance from the vehicle is a largesize vehicle such as a truck, compared to when the type of the othervehicle is a small size vehicle. The anxiety elicitation situationdetermination unit 30 may calculate the anxiety elicitation degree as alarge value when the type of other vehicle positioned within a certaindistance from the vehicle is a wide vehicle such as a luxury car,compared to when the type of other vehicle is a small size vehicle.

The anxiety elicitation situation determination unit 30 may calculatethe anxiety elicitation degree as a large value when the type of othervehicle positioned within a certain distance from the vehicle is amotorcycle, compared to when the type of the other vehicle is a smallsize vehicle. The anxiety elicitation situation determination unit 30may calculate the anxiety elicitation degree as a larger value as thenumber of other vehicles present within a certain distance from thevehicle increases. The anxiety elicitation situation determination unit30 may calculate the anxiety elicitation degree as a larger value as anoise level (for example, decibel) of the sound around the vehicle ishigher. The anxiety elicitation situation determination unit 30 maycalculate the anxiety elicitation degree as a larger value when theapproaching sound of a large vehicle is detected, compared to when theapproaching sound of a large vehicle is not detected. The anxietyelicitation situation determination unit 30 may calculate the anxietyelicitation degree as a larger value when a siren sound of a specialvehicle such as an emergency vehicle or a police vehicle is detected,compared to when the siren sound of the special vehicle is not detected.The anxiety elicitation situation determination unit 30 may calculatethe anxiety elicitation degree as a large value when there is a soundhaving noise level equal to or higher than a noise threshold value evenif the sound is generated from a construction site or the like, comparedto when there is no sound having noise level equal to or higher than thenoise threshold value.

In addition, the anxiety elicitation situation determination unit 30 maydetermine the anxiety elicitation situation by collating the externalenvironment of the vehicle with data in a determination databaseprepared in advance. In the determination database, for example, theexternal environment of the vehicle which is determined as the anxietyelicitation situation is stored as data. For example, when the externalenvironment (the image captured by the camera, the arrangement of othervehicles around the vehicle detected by the radar sensor, and the like)of the vehicle matches the data in the determination database, theanxiety elicitation situation determination unit 30 determines that thevehicle is in the anxiety elicitation situation. The method forgenerating the determination database is not particularly limited.

The warning control unit 31 performs various warnings to the driverduring autonomous driving. The warning control unit 31 performs variouswarnings by transmitting various control signals to the HMI 10. Thewarning is performed by at least one of the image display on the display10 a, the voice output from the speaker 10 b, and the output of thevibration by the vibrator 10 c of the HMI 10. The warning may beperformed by combining two or more of the image display, the voiceoutput, and the vibration.

The warning control unit 31 outputs an alert under certain conditions.Specifically, the warning control unit 31 outputs the alert when thenormal driving situation determination unit 27 determines thatautonomous driving is in the normal driving situation, the distrustdetermination unit 29 determines that the driver is in the systemdistrust state, and the anxiety elicitation situation determination unit30 determines that the vehicle during autonomous driving is in theanxiety elicitation situation.

The alert described above is an alert to eliminate the system distruststate for the driver. The alert is output according to the externalenvironment of the vehicle. The content of the alert is not limited aslong as the alert can contribute to eliminate the driver's systemdistrust state as much as possible. The alert may be a more thoroughalert as compared to when it is determined that the driver is not in thesystem distrust state, to eliminate the system distrust state for thedriver. Examples of the thorough alert include an early alert thatperforms attention awakening to the driver that there is a risk such asobstacles, prior to the normal attention awakening alert.

The alert includes at least one of the alert by the display, the alertby the sound, and the alert by the vibration. The alert may be performedby combining two or more of the alert by the display, the alert by thesound, and the alert by the vibration.

The alert by the display includes the image display by the display 10 aof the HMI 10. The alert by the display may be a projection display onthe windshield of the vehicle using a head-up display. The alert by thedisplay may be an image display on a multi-information display, or animage display on a blind spot monitor provided on a side mirror of thevehicle. The alert by the display may include an image display on ascreen such as a driver's smartphone communicating with the vehicle viathe in-vehicle communication unit 8. The display content may bedisplayed with an icon or displayed with a text. The display content isnot limited as long as the content can contribute to the elimination ofthe driver's system distrust state.

The alert by the sound includes a voice output from the speaker 10 b.The alert by the sound includes at least one of the alarm sound and thevoice. The alarm sound may be a continuous sound or an intermittentsound. The type and the content of the voice are not limited as long asthe voice can contribute to the elimination of the driver's systemdistrust state.

The alert by the vibration includes the output of vibration from thevibrator 10 c. The alert by the vibration includes at least one ofvibration of a steering unit, vibration of a driver's seat, vibration ofa driver's headrest, vibration of a driver's armrest, vibration of anaccelerator pedal, and vibration of a brake pedal.

For example, the warning control unit 31 does not output the alert whenthe normal driving situation determination unit 27 determines thatautonomous driving is not in the normal driving situation, when thedistrust determination unit 29 determines that the driver is not in thesystem distrust state, or when the anxiety elicitation situationdetermination unit 30 determines that the vehicle during autonomousdriving is not in the anxiety elicitation situation.

The warning control unit 31 outputs the alert in accordance with theexternal environment of the vehicle when the normal driving situationdetermination unit 27 determines that autonomous driving is in thenormal driving situation, the distrust determination unit 29 determinesthat the driver is in the system distrust state, and the anxietyelicitation situation determination unit 30 determines that the vehicleduring autonomous driving is in the anxiety elicitation situation. Thewarning control unit 31 does not output the alert when the externalenvironment is not to be notified to the driver. Examples of theexternal environment to be notified to the driver include an environmentin which the obstacles are present in front of the vehicle, and a roadtraffic environment to be noted in front of the vehicle. Examples of theexternal environment to be notified to the driver include an environmentin which the pedestrians or bicycles are present around the vehicle.

Processing of Autonomous Driving System

Next, the processing by autonomous driving system 100 in the presentembodiment will be described with reference to the drawings.

Autonomous Driving Processing

FIG. 4 is a flowchart illustrating an example of the autonomous drivingprocessing. The autonomous driving processing illustrated in FIG. 4 isperformed when autonomous driving of the vehicle is started.

As illustrated in FIG. 4, as S10, the ECU 20 of the autonomous drivingsystem 100 recognizes the position of the vehicle on the map by usingthe vehicle position recognition unit 21. The vehicle positionrecognition unit 21 recognizes the position of the vehicle on the mapbased on the position information in the GPS receiver 1 and the mapinformation in the map database 4. In addition, the vehicle positionrecognition unit 21 may estimate the position of the vehicle on the mapusing SLAM technology or the like.

In S12, the ECU 20 recognizes the external environment of the vehicle byusing the external environment recognition unit 22. The externalenvironment recognition unit 22 recognizes the external environment ofthe vehicle based on the result of the detection performed by theexternal sensor 2.

In S14, the ECU 20 recognizes the travel state of the vehicle by usingthe travel state recognition unit 23. The travel state recognition unit23 recognizes the state of the traveling vehicle based on the result ofthe detection performed by the internal sensor 3.

In S16, the ECU 20 generates a trajectory for autonomous driving byusing the trajectory generation unit 24. The trajectory generation unit24 generates the trajectory for autonomous driving based on thedestination set in advance, the map information, the position of thevehicle on the map, the external environment of the vehicle, and thetravel state of the vehicle.

In S18, the ECU 20 performs autonomous driving by using the vehiclecontrol unit 25. The vehicle control unit 25 performs autonomous drivingof the vehicle based on the map information, the position of the vehicleon the map, the external environment of the vehicle, the travel state ofthe vehicle, and the trajectory.

Alert Output Processing

FIG. 5 is a flowchart illustrating an example of the alert outputprocessing. The alert output processing illustrated in FIG. 5 isperformed during autonomous driving of the vehicle. The alert outputprocessing may be started after a certain period of time has elapsedsince autonomous driving of the vehicle is started or after traveling acertain distance.

As illustrated in FIG. 5, as S20, the ECU 20 calculates the systemconfidence degree of autonomous driving by using the system confidencedegree calculation unit 26. The system confidence degree calculationunit 26 calculates the system confidence degree based on at least one ofthe position of the vehicle on the map, the external environment of thevehicle, the travel state of the vehicle, and the trajectory of thevehicle.

In S22, the ECU 20 determines whether or not autonomous driving is inthe normal driving situation by using the normal driving situationdetermination unit 27. The normal driving situation determination unit27 determines whether or not autonomous driving is in the normal drivingsituation, based on at least one of the position of the vehicle on themap, the external environment of the vehicle, the travel state of thevehicle, and the trajectory of the vehicle. If it is determined thatautonomous driving is in the normal driving situation (YES in S22), theECU 20 makes the process proceed to S24. If it is determined thatautonomous driving is not in the normal driving situation (NO in S22),the ECU 20 ends the current processing. Thereafter, when autonomousdriving is continued, the ECU 20 repeats the processing from S20 againafter a predetermined time has elapsed.

In S24, the ECU 20 determines whether or not the driver is in the systemdistrust state by using the distrust determination unit 29. The distrustdetermination unit 29 determines whether or not the driver is in thesystem distrust state based on the driving situation of the driver.Details of the system distrust state determination processing will bedescribed below.

If it is determined that the driver is in the system distrust state (YESin S24), the ECU 20 makes the process proceed to S26. If it isdetermined that the driver is not in the system distrust state (NO inS24), the ECU 20 ends the current processing. Thereafter, whenautonomous driving is continued, the ECU 20 repeats the processing fromS20 again after a predetermined time has elapsed.

In S26, the ECU 20 determines whether or not the vehicle duringautonomous driving is in the anxiety elicitation situation by using theanxiety elicitation situation determination unit 30. For example, basedon the image captured by the camera that captures the front of thevehicle, if the area of the moving object in the captured image is equalto or greater than the anxiety elicitation threshold value, the anxietyelicitation situation determination unit 30 determines that the vehicleduring autonomous driving is in the anxiety elicitation situation. Thedetails of the anxiety elicitation situation determination processingwill be described below.

If it is determined that the vehicle during autonomous driving is in theanxiety elicitation situation (YES in S26), the ECU 20 makes the processproceed to S28. If it is determined that the vehicle during autonomousdriving is not in the anxiety elicitation situation (NO in S26), the ECU20 ends the current processing. That is, The ECU 20 does not output thealert when it is determined that the vehicle during autonomous drivingis in the anxiety elicitation situation. Thereafter, when autonomousdriving is continued, the ECU 20 repeats the processing from S20 againafter a predetermined time has elapsed.

In S28, the ECU 20 outputs the alert by using the warning control unit31. The warning control unit 31 outputs the alert by transmitting acontrol signal to the HMI 10. Thereafter, the ECU 20 ends the currentprocessing. The ECU 20 repeats the processing from S20 again after apredetermined standby time has elapsed.

System Distrust State Determination Processing

FIG. 6 is a flowchart illustrating an example of the system distruststate determination processing. The system distrust state determinationprocessing corresponds to the processing in S24 illustrated in FIG. 5.

As illustrated in FIG. 6, ECU 20 recognizes the driving action time byusing the driver situation recognition unit 28 as S30. The driversituation recognition unit 28 recognizes the driving action time of thedriver based on, for example, at least one of the driver's operationdetected by the driving operation detection unit 5 and the driver imagecaptured by the driver monitor camera 6.

The ECU 20 determines whether or not the length of the driving actiontime of the driver in a certain period is equal to or longer than thedriving action threshold value by using the distrust determination unit29 as S32. If it is determined that the length of the driving actiontime of the driver in a certain period is equal to or longer than thedriving action threshold value (YES in S32), the ECU 20 makes theprocess proceed to S34. If it is determined that the length of thedriving action time of the driver in a certain period is not equal to orlonger than the driving action threshold value (NO in S32), the ECU 20makes the process proceed to S36.

In S34, the ECU 20 determines that the driver is in the system distruststate by using the distrust determination unit 29. In S36, the ECU 20determines that the driver is not in the system distrust state by usingthe distrust determination unit 29.

Reference Reaction Delay Time Storage Processing

FIG. 7A is a flowchart illustrating an example of the reference reactiondelay time storage processing. The reference reaction delay time storageprocessing is the premise processing of another example of the systemdistrust state determination processing described below. The referencereaction delay time storage processing is performed during autonomousdriving of the vehicle.

As illustrated in FIG. 7A, as S40, the ECU 20 determines whether or notthe warning is performed by using the warning control unit 31. Thewarning control unit 31 performs warning to the driver by transmitting acontrol signal to the HMI 10. The warning to be determined may belimited to the warning with respect to the changes in the externalenvironment of the vehicle. If the warning is performed (YES in S40),the ECU 20 makes the process proceed to S42. If the warning is notperformed (NO in S40), the ECU 20 ends the current processing.Thereafter, when autonomous driving is continued, the ECU 20 repeats theprocessing from S40 again after a predetermined time has elapsed.

In S42, the ECU 20 recognizes the warning reaction delay time of thedriver to the warning by using the driver situation recognition unit 28.The driver situation recognition unit 28 recognizes the time from thewarning output to the time of the recognition of the driver's reactionas the warning reaction delay time of the driver to the warning.

In S44, the ECU 20 stores the warning reaction delay time of the driveras a reference reaction delay time by using the distrust determinationunit 29. The distrust determination unit 29 may store the referencereaction delay time in a storage device connected to the ECU 20.

Thereafter, the ECU 20 ends the current processing. The ECU 20 mayupdate the reference reaction delay time by repeating the processingfrom S40 again after a predetermined standby time has elapsed.

Another Example of System Distrust State Determination Processing

FIG. 7B is a flowchart illustrating another example of the systemdistrust state determination processing. The system distrust statedetermination processing corresponds to the processing in S24illustrated in FIG. 5.

As illustrated in FIG. 7B, as S50, the ECU 20 detects the changes in theexternal environment of the vehicle by using the external environmentrecognition unit 22. The external environment recognition unit 22detects the changes in the external environment of the vehicle based onthe result of the detection performed by the external sensor 2. If thechanges in the external environment of the vehicle are detected (YES inS50), the ECU 20 makes the process proceed to S52. If the changes in theexternal environment of the vehicle are not detected (NO in S50), theECU 20 ends the current processing. Thereafter, when autonomous drivingis continued, the ECU 20 repeats the processing from S50 again after apredetermined time has elapsed.

In S52, the ECU 20 recognizes the reaction delay time of the driver tothe changes in the external environment of the vehicle by the driversituation recognition unit 28. The driver situation recognition unit 28recognizes the reaction delay time of the driver to the changes in theexternal environment of the vehicle based on at least one of operationby the driver detected by the driving operation detection unit 5 and thedriver image captured by the driver monitor camera 6.

In S54, the ECU 20 determines whether or not the difference between thereaction delay time of the driver and the reference reaction delay timeis equal to or greater than the distrust threshold value by using thedistrust determination unit 29. The difference between the reactiondelay time of the driver and the reference reaction delay time refers toa difference obtained by subtracting the reaction delay time of thedriver from the reference reaction delay time. If it is determined thatthe difference between the reaction delay time of the driver and thereference reaction delay time is equal to or greater than the distrustthreshold value (YES in S54), the ECU 20 makes the process proceed toS56. If it is determined that the difference between the reaction delaytime of the driver and the reference reaction delay time is not equal toor greater than the distrust threshold value (NO in S54), the ECU 20makes the process proceed to S58.

In S56, the ECU 20 determines that the driver is in the system distruststate by using the distrust determination unit 29. In S58, the ECU 20determines that the driver is not in the system distrust state by usingthe distrust determination unit 29.

When both the determination processing of FIG. 6 and the determinationprocessing of FIG. 7B are performed, even if it is determined that thedriver is in the system distrust state in any one determinationprocessing and it is determined that the driver is not in the systemdistrust state in the other determination processing, the ECU 20 mayprioritize the determination result of the system distrust state.Alternatively, the ECU 20 may prioritize the result of the determinationprocessing of FIG. 6, and may prioritize the result of the determinationprocessing of FIG. 7B. Also, the ECU 20 does not necessarily need toperform both the determination processing of FIG. 6 and thedetermination processing of FIG. 7B.

Anxiety Elicitation Situation Determination Processing

FIG. 8 is a flowchart illustrating an example of the anxiety elicitationsituation determination processing. The anxiety elicitation situationdetermination processing corresponds to the processing in S26illustrated in FIG. 5.

As illustrated in FIG. 8, as S60, the ECU 20 determines whether or notthe area of the moving object in the image captured by the camera thatimages the front of the vehicle is equal to or greater than the anxietyelicitation threshold value by using the anxiety elicitation situationdetermination unit 30. The anxiety elicitation situation determinationunit 30 performs the above-described determination based on the imagecaptured by the camera that images the front of the vehicle. If it isdetermined that the area of the moving object in the image captured bythe camera is equal to or greater than the anxiety elicitation thresholdvalue (YES in S60), the ECU 20 makes the process proceed to S62. If itis determined that the area of the moving object in the image capturedby the camera is not equal to or greater than the anxiety elicitationthreshold value (NO in S60), the ECU 20 makes the process proceed toS64.

In S62, the ECU 20 determines that the vehicle during autonomous drivingis in the anxiety elicitation situation by using the anxiety elicitationsituation determination unit 30. In S64, the ECU 20 determines that thevehicle during autonomous driving is not in the anxiety elicitationsituation by the anxiety elicitation situation determination unit 30.

Operational Effect of Autonomous Driving System

According to the autonomous driving system 100 according to the presentembodiment described above, the alert is output in accordance with theexternal environment of the vehicle when the normal driving situationdetermination unit 27 determines that autonomous driving is in thenormal driving situation, the distrust determination unit 29 determinesthat the driver is in the system distrust state, and the anxietyelicitation situation determination unit 30 determines that the vehicleduring autonomous driving is in the anxiety elicitation situation. Inthis way, in the autonomous driving system 100, it is possible toappropriately eliminate the system distrust state of the driver duringautonomous driving by encouraging the driver who is in the systemdistrust state by outputting the alert in accordance with the externalenvironment while ensuring that autonomous driving is in the normaldriving situation. According to the autonomous driving system 100, sincethe driver may feel anxious about the external environment of thevehicle when it is determined that the vehicle is in the anxietyelicitation situation, it is possible to appropriately eliminate thesystem distrust state of the driver by outputting the alert.

Furthermore, according to the autonomous driving system 100, bydetermining the normal driving situation of autonomous driving by usingthe system confidence degree regarding autonomous driving, it ispossible to appropriately determine whether or not autonomous driving isin the normal driving situation compared to when the system confidencedegree is not used.

In addition, according to the autonomous driving system 100, since thedriver is likely to feel more anxious about the traveling of the vehicleas the area of the obstacle that occupies the field of view of thedriver seeing the front of the vehicle increases, if the area of themoving object in the image captured by the camera that images the frontof the vehicle is equal to or greater than the anxiety elicitationthreshold value, it is possible to determine that the vehicle duringautonomous driving is in the anxiety elicitation situation.

As described above, the embodiments of the present disclosure weredescribed, however, the present disclosure is not limited to theembodiments described above. In addition to the above-describedembodiments, the present disclosure can be embodied in various formsincluding various modifications and improvements based on the knowledgeof those skilled in the art.

The distrust determination unit 29 may determine whether or not thedriver is not in the system distrust state based on the driver's drivingaction time Td when the anxiety elicitation situation determination unit30 determines that the vehicle during autonomous driving is in theanxiety elicitation situation. Since the driver is likely to be in thesystem distrust state when the ratio of the driver's driving actionunder the situation that is not the anxiety elicitation situation ishigh, the distrust determination unit 29 can determine whether or notthe driver is in the system distrust state based on the driver's drivingaction time Td under the situation that is not the anxiety elicitationsituation. The distrust determination unit 29 determines that the driveris in the system distrust state when, for example, the length of thedriving action time Td of the driver under the situation that is not theanxiety elicitation situation is equal to or longer than a firstdistrust determination threshold value.

Similarly, the distrust determination unit 29 may determine whether ornot the driver is in the system distrust state based on the non-drivingaction time Ts of the driver under the situation that is not the anxietyelicitation situation. The distrust determination unit 29 may determinethat the driver is in the system distrust state when the length of thenon-driving action time Ts of the driver under the situation that is notthe anxiety elicitation situation is shorter than a second distrustdetermination threshold value. The first distrust determinationthreshold value and the second distrust determination threshold valueare the threshold values set in advance.

The autonomous driving system 100 does not necessarily need to includethe system confidence degree calculation unit 26. That is, theautonomous driving system 100 does not necessarily need to calculate thesystem confidence degree. In this case, the normal driving situationdetermination unit 27 need only determine whether or not autonomousdriving is in the normal driving situation based on at least one of theposition of the vehicle on the map, the external environment of thevehicle, the travel state of the vehicle, and the trajectory of thevehicle, without using the system confidence degree.

The autonomous driving system 100 does not necessarily need to includethe anxiety elicitation situation determination unit 30. That is, theautonomous driving system 100 does not necessarily need to determinewhether or not the vehicle during autonomous driving is in the anxietyelicitation situation. In this case, when the normal driving situationdetermination unit 27 determines that autonomous driving is in thenormal driving situation and the distrust determination unit 29determines that the driver is in the system distrust state, the warningcontrol unit 31 outputs the alert. If the normal driving situationdetermination unit 27 determines that autonomous driving is not in thenormal driving situation, or if the distrust determination unit 29determines that the driver is not in the system distrust state, thewarning control unit 31 does not output the alert.

The driver situation recognition unit 28 may recognize the driver'sreaction to the alert after the alert is output. The warning controlunit 31 may output the alert again if the driver's reaction to the alertis not recognized. When the alert is output again, the warning controlunit 31 may output the alert strongly compared to the alert outputpreviously. The strong output is, for example, an output with a largervolume when voice output, and an output of strong luminance when imagedisplay. The strong output may be realized by changing the frequency ofthe voice and the chromaticity of the image. The distrust determinationunit 29 may determine that the system distrust state of the driver iseliminated, when the reaction of the driver to the alert is recognized.

What is claimed is:
 1. An autonomous driving system that performsautonomous driving of a vehicle and performs various warnings to adriver of the vehicle during autonomous driving, the system comprising:a vehicle position recognition unit configured to recognize a positionof the vehicle on a map; an external environment recognition unitconfigured to recognize an external environment of the vehicle; a travelstate recognition unit configured to recognize a travel state of thevehicle; a trajectory generation unit configured to generate atrajectory of the vehicle used for the autonomous driving, based on mapinformation, the position of the vehicle on the map, the externalenvironment of the vehicle, and the travel state of the vehicle; anormal driving situation determination unit configured to determinewhether or not autonomous driving is in a normal driving situation,based on at least one of the position of the vehicle on the map, theexternal environment of the vehicle, the travel state of the vehicle,and the trajectory of the vehicle; a driver situation recognition unitconfigured to recognize a driver situation including at least one of adriving action time of the driver, a non-driving action time of thedriver, and a reaction delay time of the driver with respect to a changein the external environment of the vehicle; a distrust determinationunit configured to determine whether or not the driver is in a systemdistrust state, based on a recognition result obtained by the driversituation recognition unit; and a warning control unit configured tooutput an alert in accordance with the external environment of thevehicle when the normal driving situation determination unit determinesthat autonomous driving is in the normal driving situation and thedistrust determination unit determines that the driver is in the systemdistrust state.
 2. The autonomous driving system according to claim 1,further comprising: a system confidence degree calculation unitconfigured to calculate a system confidence degree regarding theautonomous driving based on at least one of the position of the vehicleon the map, the external environment of the vehicle, the travel state ofthe vehicle, and the trajectory of the vehicle, wherein the normaldriving situation determination unit determines that autonomous drivingis not in the normal driving situation, when the system confidencedegree is lower than a normal driving threshold value.
 3. The autonomousdriving system according to claim 1, further comprising: an anxietyelicitation situation determination unit configured to determine whetheror not the vehicle during autonomous driving is in an anxietyelicitation situation based on the external environment of the vehicle,wherein the warning control unit outputs the alert when the anxietyelicitation situation determination unit determines that the vehicle isin the anxiety elicitation situation in case where the normal drivingsituation determination unit determines that autonomous driving is inthe normal driving situation and the distrust determination unitdetermines that the driver is in the system distrust state, and does notoutput the alert when the anxiety elicitation situation determinationunit determines that the vehicle is not in the anxiety elicitationsituation, in case where the normal driving situation determination unitdetermines that autonomous driving is in the normal driving situationand the distrust determination unit determines that the driver is in thesystem distrust state.
 4. The autonomous driving system according toclaim 3, wherein the anxiety elicitation situation determination unitdetermines that the vehicle during autonomous driving is in the anxietyelicitation situation, if an area of a moving object in a captured imageby a camera that images the front of the vehicle as the externalenvironment of the vehicle is equal to or greater than an anxietyelicitation threshold value.